The course is divided in three parts. In the first part the nature of the geographical data is discussed whilst the identification of spatial patterns is the focus in the second part of the course. The third part refers to confirmatory spatial data analysis using regression analysis, its applications and assessment (case study).
PART I – Lecture 1 -Thinking spatially: introduction to GIScience, Lecture 2 -The nature of spatial data, Lecture 3-Data quality.
PART II – Lecture 4 -Spatial structure of spatial data, Lecture 5 -Non-parametric methods of spatial interpolation, Lecture 6 - Areal interpolation. Lecture 7 - Exploratory spatial data analysis (ESDA). cluster detection methods and Lecture 8 - Introduction to confirmatory analysis.
PART III -Lecture 9 -Regression analysis. Lecture 10-Implementing space in social sciences: a summary, Lectures 11-12-Applications, Project (study case) and Project presentation.
The first week provides students with basic introduction to the course and tools. A set of introductory practical exercises will be provided to those unfamiliar with ArcGis, GeoDa and ScanStat. The first chapters in Haining (latest edition) should be read by the students before the first class (available in BILDA three weeks before the course starts).